Monday, 27 January 2014

Over christmas I had chance to read the book Running with The Kenyans by Adharanand Finn. In short the book is about a British guy's experience of immersing himself for six months in the Kenyan running culture. A recurring theme throughout the book is the question of why Kenyan's have come to dominate long distance running. The answer clearly depends on a number of things like high altitude, running to school etc. But the main thing seems to be a culture of running. Kenyans run because that is what Kenyans do. So, what has that got to do with economics?

There can be no doubt that Kenyan athletes take running very seriously. In other words they put in hours and hours of training (and perhaps more importantly put in hours and hours of dedicated rest). An economist would think of this as human capital formation. All the hours of dedication to running are about the person improving their ability to run fast so that he or she can eventually win some races and make some money and get some reward. It is a person's investment in future productivity. Very few Kenyan athletes go on, however, to win races and make money. For most the investment in running does not pay off in terms of increased productivity. Currrent economic theory is very poorly placed to explain outcomes like this.

The textbook model of human capital formation primarily focuses on how much to invest in human capital formation. Implicit in this seems to be an assumption of 'linearity' from less well educated and less productive to well educated and more productive. For example, years of schooling and achievements at school or university are seen as good measures of productivity. Reality is, however, far more multi-dimensional that this. Put another way, human capital is not always very transferable. For example, a Kenyan who has spent years training to be a runner is not going to do well as an economics professor. And a Brit who has spent years doing economics is not going to win many marathons. Someone investing in human capital not only, therefore, has to decide how much to invest they also have to decide what to invest in. Should they train to be a runner, economist, physicist, pianist, actor, writer, .....
Once we recognize the multi-dimensional nature of human capital we realize the matching problem inherent in labour supply. Society is only willing to support so many Kenyan athletes, or concert pianists, or economists. Inefficiency in solving this matching problem is why most Kenyans, despite being faster than the best British athletes, do not make it as professional runners. And reasons we end up with such inefficiencies are not hard to find. Most crucially, human capital formation takes a long time and is basically irreversible. People cannot, therefore, learn from experience. And how is a teenager supposed to know where best their future lies? Things are made even more complicated by the winner-take-all nature of many of the professions that require high human capital. Because only a handful of athletes make serious money the law of large numbers 'smoothing' effect does not come into play. This results in a big drop between being good enough and being not quite good enough. Again, how can a teenager know they are going to be good enough? Do not expect good choices.
I got interested in the matching nature of the labour market in the early days of my PhD (with one paper to show for it). At that stage I felt a frustration at how poorly the matching within the labour market were understood. From what I can tell, not much has come along to improve our understanding. So, why are economists not studying this more? I would suggest an unwillingness to accept the basic ad-hoc nature of the labour market is the main issue. If I look back at my life: there was no grand plan to be an economist or invest in specific types of human capital; there were though lots of events that could have easily been different, and if they had been different I would not have been an economist. Most people surely stumble through life in a similar way. Acknowledging this is a big step from the standard economic models of utility maximization. But it can help explain why Kenyans go out running despite little chance of winning the New York Marathon. It can also help us better understand unemployment, skills gaps, and income inequality.

Friday, 17 January 2014

We've not long got back from a skiing holiday in the Swiss Alps. And one thing that caught my attention (particular as our trip coincided with Michael Schumacher's accident) was that everyone skiing was wearing a helmet. When I was learning to ski 25 years ago nobody wore a helmet. So, how did society go from 0% wearing a helmet to 100% wearing one?

The obvious answers if you read the economic textbook would be that: (i) ski helmets have got cheaper, or (ii) ski helmets have become better - lighter, safer etc., or (iii) skiers are better informed about the benefits of wearing a helmet. Personally, I think we can safely ignore all three of these as the main causal factor. To argue the point I would compare skiing with cycling and rock climbing. Over the timespan I'm looking at here I would guess that helmet usage in cycling and rock climbing has stayed pretty much constant - and nearer to 50% than 0 or 100%. Yet skiing helmets are essentially somewhere in-between cycling and climbing helmets. So, if either (i), (ii) or (iii) are the reason so many people are wearing ski helmets I would expect to see a similar change in the proportion of people wearing cycle and climbing helmets. And that has not happened.

In order to explain the shift in helmet usage I would instead look to conformity. I think the main reason skiers where helmets is because other skiers wear helmets. This can easily explain a shift from 0 to 100%: We go from an equilibrium of no one wearing a helmet because no one wears a helmet, to an equilibrium where everyone wears a helmet because everyone wears a helmet. It is also easy to explain the difference between skiing and cycling and rock climbing: A ski resort is a 'confined space' where you are surrounded by skiers wearing helmets, while a cyclist or climber can easily not meet other cyclists or climbers all day long. This lack of exposure to others can be expected to dim the influence of conformity.

But what does conformity really mean? It is tradition to distinguish between informational conformity and behavioural conformity. Informational conformity would say you wear a helmet, on seeing others wearing them, because you think they must be well informed on the safety benefits of wearing helmets. Behavioural conformity would say you wear a helmet so as to not be the odd one out. My hunch is that a third type of conformity is also at play here - I will call it reflectional conformity. And the basic idea is that seeing others doing something different makes you reflect more on your own decision. So, seeing others wearing helmets makes you reflect on the potential losses of you not wearing a helmet. This means that your choice is not directly influenced by observing others. It is more that observing others doing something different indirectly makes you reflect much more on the decision you are making. And when you think about, a helmet definitely seems worth buying.

As far as I am aware reflectional conformity is a new idea. But I can point to some evidence it exists because in a recent experiment with Thomas Singh we saw clear signs of it. The experiment was set up to see whether subjects were more cooperative if they saw what others were doing. We found that observing what others were doing had a big effect on cooperation. And it do so because subjects were more responsive to own experience. In short, what we saw looked much more like reflectional conformity than behavioural or informational conformity.